Abstract: A semiconductor device includes a substrate, at least one via, a liner layer and a conductive layer. The substrate includes an electronic circuitry. The at least one via passes through the substrate. The at least one via includes a plurality of concave portions on a sidewall thereof. The liner layer fills in the plurality of concave portions of the at least one via. The conductive layer is disposed on the sidewall of the at least one via, covers the liner layer, and extends onto a surface of the substrate. The thickness of the conductive layer on the sidewall of the at least one via is varied.

Abstract: A plurality of devices for testing, connected in series using one or more redistribution layers (RDLs), are used to perform a semiconductor device test on a plurality of dies. As a result, the semiconductor device test may support thousands of gross dies per wafer or greater (e.g., 10,000 dies or greater). Furthermore, the RDL(s) may be removed after use. In some implementations, the devices for testing corresponding to the dies may execute the semiconductor device test sequentially. Accordingly, test data may be generated and may include a bit sequence, where a first bit in the bit sequence indicates an overall outcome for the test and one or more subsequent bits in the bit sequence indicate respective outcomes for each semiconductor dies or for each line of the semiconductor device test.

Abstract: A semiconductor structure is provided. The semiconductor structure includes a substrate, a diode region, and a dummy stripe. The substrate has a first surface. The diode region is in the substrate. The diode region includes a first implant region of a first conductivity type approximate to the first surface, and a second implant region of a second conductivity type approximate to the first surface and surrounded by the first implant region. The dummy stripe is on the first surface and located between the first implant region and the second implant region. A method for manufacturing a semiconductor structure is also provided.

Abstract: A semiconductor structure is provided. The semiconductor structure includes a substrate, a diode region, and a dummy stripe. The substrate has a first surface. The diode region is in the substrate. The diode region includes a first implant region of a first conductivity type approximate to the first surface, and a second implant region of a second conductivity type approximate to the first surface and surrounded by the first implant region. The dummy stripe is on the first surface and located between the first implant region and the second implant region. A method for manufacturing a semiconductor structure is also provided.

Abstract: A bipolar transistor includes a substrate having a first well with a first dopant type; and a split collector region in the substrate, the split collector region including a highly doped central region having the first dopant type, and a lightly doped peripheral region having a second dopant type, opposite the first dopant type, wherein the lightly doped peripheral region surrounds the highly doped central region, a dopant concentration of the lightly doped peripheral region ranges from about 5×1012 ions/cm3 to about 5×1013 ions/cm3, and the lightly doped peripheral region has a same maximum depth as the highly doped central region.

Abstract: A mobile epidemic prevention and disinfection robot includes a body and a control system installed on the body. The body includes a mobile base, a dust collection module, a disinfection system, a temperature detection system, and a delivery system. The delivery system includes two robot arms and a storage box. The control system includes a control module, a path planning module, and an obstacle dodge module. The control module is used to control the movement of the mobile epidemic prevention and disinfection robot, and the two robot arms to perform corresponding actions. The path planning module plans the optimal movement information of the mobile epidemic prevention and disinfection robot from the current position to a destination according to a three-dimensional map. The obstacle dodge module controls the mobile epidemic prevention and disinfection robot to dodge obstacles.

Abstract: A bipolar transistor includes a substrate having a first well with a first dopant type; and a split collector region in the substrate, the split collector region including a highly doped central region having the first dopant type, and a lightly doped peripheral region having a second dopant type, opposite the first dopant type, wherein the lightly doped peripheral region surrounds the highly doped central region, a dopant concentration of the lightly doped peripheral region ranges from about 5×1012 ions/cm3 to about 5×1013 ions/cm3, and the lightly doped peripheral region has a same maximum depth as the highly doped central region.

Abstract: A method of making a bipolar transistor includes patterning a first photoresist over a collector region of the bipolar transistor, the first photoresist defining a first opening. The method further includes performing a first implantation process through the first opening. The method further includes patterning a second photoresist over the collector region, the second photoresist defining a second opening different from the first opening. The method further includes performing a second implantation process through the second opening, wherein a dopant concentration resulting from the second implantation process is different from a dopant concentration resulting from the first implantation process.

Abstract: An autonomous mobile device includes a map interpretation module, an image collection module, an image collection module, an artificial marker identification module, a personal guidance module, a voice input module and a control module. The image collection module collects an image in front of the autonomous mobile device and form an image signal. The artificial marker identification module receives the image signal and identifies the artificial marker in the image to achieve a positioning of the autonomous mobile device. The personal guidance module activates a personal guidance mode of the autonomous mobile device, and stores a location of a guidance point and an actual movement information of the autonomous mobile device to form a guidance path. The voice input module inputs a name of the guidance path. The control module controls the autonomous mobile device to move according to the guidance path stored by the map interpretation module.

Abstract: The disclosure relates to an interconnecting device and system of IOT (Internet of Things). The interconnecting device is configured to interconnect different IOT platforms or interconnect a IOT platform with a robot. The interconnecting device comprises a hardware and a software comprising a control module, a communication module and a conversion module. The conversion module is configured to convert the message between different IOT platforms or between the IOT platform and the robot. The system of IOT comprises at least one IOT platform and the interconnecting device. The interconnecting device can interconnect different IOT platforms or interconnect a IOT platform with a robot conveniently.

Abstract: The disclosure relates to a face recognition system. The face recognition system includes a camera module configured to acquire face recognition information of a target object; a feature point recognition module configured to select facial feature points; a displacement output module configured to output a displacement and azimuth of the camera module during acquiring the face recognition information at different positions; a distance calculation module configured to calculate depth distances between the facial feature points and the displacement between the different positions; and a face recognition module configured to judge whether the target object is the target user. A face recognition method is also related.

Abstract: A substrate for an integrated circuit includes a device wafer having a raw carrier concentration and an epitaxial layer disposed over the device wafer. The epitaxial layer has a first carrier concentration. The first carrier concentration is higher than the raw carrier concentration.

Abstract: An automatic guiding system for analyzing pavement curvature in or on an autonomous mobile device comprises an image acquisition module, a pavement curvature analysis module, a posture sensing module, and a pavement curvature database. The image acquisition module collects pavement curvature images as the autonomous mobile device moves. The pavement curvature analysis module processes the pavement curvature images, and extracts contour information of the pavement curvature images. The posture sensing module continuously senses the posture of the autonomous mobile device. The pavement curvature database is configured to stores the contour information and the posture.

Abstract: An autonomous mobile device includes a map interpretation module, an image collection module, an image collection module, an artificial marker identification module, a personal guidance module, a voice input module and a control module. The image collection module collects an image in front of the autonomous mobile device and form an image signal. The artificial marker identification module receives the image signal and identifies the artificial marker in the image to achieve a positioning of the autonomous mobile device. The personal guidance module activates a personal guidance mode of the autonomous mobile device, and stores a location of a guidance point and an actual movement information of the autonomous mobile device to form a guidance path. The voice input module inputs a name of the guidance path. The control module controls the autonomous mobile device to move according to the guidance path stored by the map interpretation module.

Abstract: An autonomous mobile device with computer vision positioning system comprises a map interpretation module, an image collection module, an artificial marker identification module, a path planning module, and an obstacle dodging module. The map interpretation stores a map of a desired moving area and a map description file corresponding to the map. The image collection module collects an image in front of the autonomous mobile device during movement in the desired moving area and form a image signal. The artificial marker identification module receives the image signal outputted by the image collection module and identifies the plurality of artificial markers of the image to achieve a positioning. The path planning module plans an optimal movement information of the autonomous mobile device moving between the plurality of artificial markers. The obstacle dodging module controls the autonomous mobile device to dodge an obstacle autonomously.

Abstract: An apparatus for autonomously modifying environment information comprises an autonomous mobile device, a data storage module, an image collection module, an artificial marker identification module, a data recording module, a data analysis module, a data modification module, and a plurality of artificial markers. The image collection module is used to collect an image and transmit the image to the artificial marker identification module. The artificial marker identification module receives the images and identifies a plurality of artificial markers of the image to achieve a positioning. The data recording module records a path surface environment change information and a movement information. The data analysis module analyzes the movement information to achieve an optimal movement information. The data modification module receives the path surface environment change information and the optimal movement information to modify the map and the map description file stored in the data storage module.

Abstract: The disclosure relates to an interconnecting device and system of IOT (Internet of Things). The interconnecting device is configured to interconnect different IOT platforms or interconnect a IOT platform with a robot. The interconnecting device comprises a hardware and a software comprising a control module, a communication module and a conversion module. The conversion module is configured to convert the message between different IOT platforms or between the IOT platform and the robot. The system of IOT comprises at least one IOT platform and the interconnecting device. The interconnecting device can interconnect different IOT platforms or interconnect a IOT platform with a robot conveniently.

Abstract: A method of making a bipolar transistor includes patterning a first photoresist over a collector region of the bipolar transistor, the first photoresist defining a first opening. The method further includes performing a first implantation process through the first opening. The method further includes patterning a second photoresist over the collector region, the second photoresist defining a second opening different from the first opening. The method further includes performing a second implantation process through the second opening, wherein a dopant concentration resulting from the second implantation process is different from a dopant concentration resulting from the first implantation process.

Abstract: The disclosure relates to a face recognition system. The face recognition system includes a camera module configured to acquire face recognition information of a target object; a feature point recognition module configured to select facial feature points; a displacement output module configured to output a displacement and azimuth of the camera module during acquiring the face recognition information at different positions; a distance calculation module configured to calculate depth distances between the facial feature points and the displacement between the different positions; and a face recognition module configured to judge whether the target object is the target user. A face recognition method is also related.

Abstract: An automatic guiding system for analyzing pavement curvature in or on an autonomous mobile device comprises an image acquisition module, a pavement curvature analysis module, a posture sensing module, and a pavement curvature database. The image acquisition module collects pavement curvature images as the autonomous mobile device moves. The pavement curvature analysis module processes the pavement curvature images, and extracts contour information of the pavement curvature images. The posture sensing module continuously senses the posture of the autonomous mobile device. The pavement curvature database is configured to stores the contour information and the posture.